Our long-term objective is to understand the complex network of genetic interactions that control gene expression underlying the processes of normal development, disease and evolution. At the Berkeley Drosophila Genome Project (BDGP), we have established a gene expression resource for Drosophila development that contains spatial and temporal embryonic expression patterns, annotations of the patterns using a standardized, controlled vocabulary, based on an anatomical ontology and a standardized virtual representation of the patterns. We created tools to identify similar, partially overlapping or anti-correlated expression. Our database currently contains over 100,000 annotated images showing expression patterns generated using in-situ hybridization of staged whole-mounted embryos for approximately 60% (8500) of the protein-coding genes in the Drosophila genome. We propose to: (1) obtain expression patterns for as many of the remaining 40% of the protein-coding genes as possible, (2) develop fully automatic image acquisition with a motorized microscope and analysis pipeline to accelerate data collection and in preparation for high-throughput studies, (3) continue advancements and refinements to our virtual image representation and create web-tools and interfaces for the research community to conduct analysis with our dataset and uploaded images and (4) characterize and analyze expression patterns of conserved regulatory modules from transcription factors. The primary resource for generation of RNA probes is our Drosophila Gene Collection (DGC), which currently contains cDNA clones corresponding to 88% of the annotated genes. To capture expression patterns for genes that do not have a representative cDNA clone (12%), we used gene-specific PCR products to generate RNA probes in 96- well format. The gene expression data produced by our study will provide fundamental information for elaborating the function of the 13,831 protein-coding genes in Drosophila and will aid in elucidating the function of the homologous genes in other eukaryotes, including humans. Genome wide association studies have shown fundamental roles for regulatory regions and gene expression in human diseases. The functional analysis of regulatory regions will provide novel insights into the developmental roles of transcription factors. In addition, the integration of the gene expression data with regulatory and gene sequences will promote research to discover networks of regulatory interactions.